乐胖代购免代理版

{"id":"https://openalex.org/W4386363039","doi":"https://doi.org/10.1109/access.2023.3311023","title":"Local Path Planning: Dynamic Window Approach With Q-Learning Considering Congestion Environments for Mobile Robot","display_name":"Local Path Planning: Dynamic Window Approach With Q-Learning Considering Congestion Environments for Mobile Robot","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386363039","doi":"https://doi.org/10.1109/access.2023.3311023"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3311023","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237217.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237217.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022934757","display_name":"Masato Kobayashi","orcid":"https://orcid.org/0000-0001-9703-2858"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"funder","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masato Kobayashi","raw_affiliation_strings":["Cybermedia Center, Osaka University, Toyonaka, Japan"],"affiliations":[{"raw_affiliation_string":"Cybermedia Center, Osaka University, Toyonaka, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112972460","display_name":"Hiroka Zushi","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"funder","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroka Zushi","raw_affiliation_strings":["Graduate School of Maritime Science, Kobe University, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Maritime Science, Kobe University, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102873917","display_name":"Tomoaki Nakamura","orcid":"https://orcid.org/0000-0002-6468-5745"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"funder","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Nakamura","raw_affiliation_strings":["Graduate School of Maritime Science, Kobe University, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Maritime Science, Kobe University, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091378169","display_name":"Naoki Motoi","orcid":"https://orcid.org/0000-0003-1536-0095"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"funder","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoki Motoi","raw_affiliation_strings":["Graduate School of Maritime Science, Kobe University, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Maritime Science, Kobe University, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.227,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":10,"citation_normalized_percentile":{"value":0.99996,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":"11","issue":null,"first_page":"96733","last_page":"96742"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9999,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9999,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9952,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9859,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.4364311}],"concepts":[{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.78450626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6858705},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.6535792},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.60630953},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5971778},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.57525784},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.50209975},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4596346},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.4364311},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41975874},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.326008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24013051},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1659975},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3311023","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237217.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14094/0100483751","pdf_url":"https://da.lib.kobe-u.ac.jp/da/kernel/0100483751/0100483751.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3311023","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10237217.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"score":0.52,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":32,"referenced_works":["https://openalex.org/W1580535863","https://openalex.org/W2117211893","https://openalex.org/W2163411428","https://openalex.org/W2177274602","https://openalex.org/W2296693324","https://openalex.org/W2626820647","https://openalex.org/W2789990415","https://openalex.org/W2890105422","https://openalex.org/W2892083874","https://openalex.org/W2892310933","https://openalex.org/W2952009315","https://openalex.org/W2955835633","https://openalex.org/W3011120880","https://openalex.org/W3035991693","https://openalex.org/W3047624789","https://openalex.org/W3086080003","https://openalex.org/W3090270894","https://openalex.org/W3126834919","https://openalex.org/W3129265343","https://openalex.org/W3134008892","https://openalex.org/W3153752809","https://openalex.org/W3172563651","https://openalex.org/W3206270475","https://openalex.org/W4210942808","https://openalex.org/W4226493205","https://openalex.org/W4290717612","https://openalex.org/W4293057543","https://openalex.org/W4294125884","https://openalex.org/W4308094108","https://openalex.org/W4309225961","https://openalex.org/W4311697006","https://openalex.org/W4313004829"],"related_works":["https://openalex.org/W3043170174","https://openalex.org/W2930076404","https://openalex.org/W2917514722","https://openalex.org/W2906946336","https://openalex.org/W2782776446","https://openalex.org/W2596413128","https://openalex.org/W2356867392","https://openalex.org/W2155948905","https://openalex.org/W2071957557","https://openalex.org/W1971413691"],"abstract_inverted_index":{"In":[0,36],"recent":[1],"years,":[2],"autonomous":[3],"mobile":[4],"robots":[5],"have":[6],"significantly":[7],"increased":[8],"in":[9,100,125],"prevalence":[10],"due":[11],"to":[12,15,66,118,168,179,195,199],"their":[13,25],"ability":[14,198],"augment":[16],"and":[17,109,157,173,192],"diversify":[18],"the":[19,39,115,134,165,201],"workforce.":[20],"One":[21],"critical":[22],"aspect":[23],"of":[24,58,159,185,203],"operation":[26],"is":[27,72],"effective":[28],"local":[29,51,204],"path":[30,52,59,71,75,205],"planning,":[31],"which":[32],"considers":[33],"dynamic":[34,67,135],"constraints.":[35,68],"this":[37,129,131],"context,":[38],"Dynamic":[40],"Window":[41],"Approach":[42],"(DWA)":[43],"has":[44],"been":[45],"widely":[46],"recognized":[47],"as":[48,104],"a":[49,56,94,148],"robust":[50],"planning.":[53,206],"DWA":[54,142],"produces":[55],"set":[57],"candidates":[60,76],"derived":[61],"from":[62,74],"velocity":[63],"space":[64],"subject":[65],"An":[69],"optimal":[70,171],"selected":[73],"through":[77,189],"an":[78],"evaluation":[79,116],"function":[80,117],"guided":[81],"by":[82],"fixed":[83,87],"weight":[84,88,136,160,174],"coefficients.":[85,161],"However,":[86],"coefficients":[89,137,175],"are":[90],"typically":[91],"designed":[92],"for":[93,141],"specific":[95],"environmental":[96,101,155,181],"context.":[97],"Consequently,":[98],"changes":[99],"conditions":[102],"such":[103],"congestion":[105],"levels,":[106],"road":[107],"width,":[108],"obstacle":[110],"density":[111],"could":[112],"potentially":[113],"lead":[114],"select":[119,170],"inefficient":[120],"paths":[121,172],"or":[122],"even":[123],"result":[124],"collisions.":[126],"To":[127],"overcome":[128],"challenge,":[130],"paper":[132],"proposes":[133],"based":[138],"on":[139],"Q-learning":[140],"(DQDWA).":[143],"The":[144,183],"proposed":[145],"method":[146],"uses":[147],"pre-learned":[149,166],"Q-table":[150,167],"that":[151,176],"comprises":[152],"robot":[153],"states,":[154],"conditions,":[156],"actions":[158],"DQDWA":[162,186],"can":[163],"use":[164],"dynamically":[169],"better":[177],"adapt":[178],"varying":[180],"conditions.":[182],"performance":[184],"was":[187],"validated":[188],"extensive":[190],"simulations":[191],"real":[193],"experiments":[194],"confirm":[196],"its":[197],"enhance":[200],"effectiveness":[202]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4386363039","counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1}],"updated_date":"2025-04-16T11:38:26.158819","created_date":"2023-09-02"}